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Peter German

Government of the United States of America - Idaho National Laboratory

Box 1625

Idaho Falls, ID 83415

United States

  • Government of the United States of America - Idaho National Laboratory

SCHOLARLY PAPERS

5

DOWNLOADS

360

TOTAL CITATIONS

0

Scholarly Papers (5)

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1.

Uncertainty-Aware Multi-Output Gaussian-Process Autoregression for Melt-Pool Dynamics and Microstructural Implications

Number of pages: 24 Posted: 25 Nov 2025
Purna Vindhya Kota, Sudipta Biswas, Peter German, Lori Graham-Brady and Somayajulu Dhulipala
Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Johns Hopkins University and Government of the United States of America - Idaho National Laboratory
Downloads 97 (742,061)

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Gaussian processes, Uncertainty quantification, Advanced manufacturing, Phase-field, Arbitrary Lagrangian-Eulerian

2.

Moose Navier-Stokes Module

Number of pages: 16 Posted: 23 May 2023
Alexander Lindsay, Guillaume Giudicelli, Peter German, John Peterson, Yaqi Wang, Ramiro Freile, David Andrs, Paolo Balestra, Mauricio Tano, Rui Hu, Ling Zou, Derek Gaston, Cody Permann and Sebastian Schunert
Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Argonne National Laboratory, Government of the United States of America - Argonne National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory and Government of the United States of America - Idaho National Laboratory
Downloads 84 (803,225)

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Navier-Stokes, finite elements, finite volumes, porous medium

3.

Moose Stochastic Tools: A Module for Performing Parallel, Memory-Efficient in Situ Stochastic Simulations

Number of pages: 14 Posted: 29 Mar 2022
Zachary Merritt Prince, Andrew E. Slaughter, Peter German, Ian Halvic, Wen Jiang, Benjamin Spencer, Somayajulu Dhulipala and Derek Gaston
Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Texas A&M University, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory and Government of the United States of America - Idaho National Laboratory
Downloads 70 (875,328)

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Stochastic, Parallel, Multiphysics, MOOSE

4.

Multiphysics Simulations of the Advanced Test Reactor using Pronghorn and Griffin

Number of pages: 31 Posted: 20 Jan 2026
Guillaume Gesmier, Peter German, Mauricio Tano, Guillaume Giudicelli, Joshua Hanophy, Namjae Choi and Zachary Merritt Prince
Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory, Government of the United States of America - Idaho National Laboratory and Government of the United States of America - Idaho National Laboratory
Downloads 55 (1,031,043)

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Advanced Test Reactor, Pronghorn, Griffin, OpenMC, Multiphysics Simulation, Accidental transients

5.

Enabling Scientific Machine Learning in MOOSE Using Libtorch

Number of pages: 16 Posted: 08 Mar 2023
Peter German and Dewen Yushu
Government of the United States of America - Idaho National Laboratory and Government of the United States of America - Idaho National Laboratory
Downloads 54 (1,052,702)

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MOOSE, Libtorch, Deep Reinforcement Learning, Scientific Machine Learning